MLOps Platform Engineer — Vertex AI & GKE Expert

Poland and Central-Eastern Europe; Polska; Remote; PLN 240,000 - 360,000; Full time

Job summary

Xebia in Europe is seeking an experienced MLOps Platform Engineer to own the company's machine learning platform infrastructure. You will manage Vertex AI, Kubeflow Pipelines, and GKE-based training and serving, building templates, CI/CD, and self-service workflows that let data scientists ship models without tickets.

You will oversee model lifecycle, feature/data flows with BigQuery and Airflow, implement GitOps, and ensure security and cost efficiency.

Qualifications

• 5+ years in MLOps or ML platform engineering.
• 2+ years owning production ML infrastructure end-to-end.
• Hands-on with GCP: Vertex AI, GKE, BigQuery.
• Strong Kubernetes expertise; can run and debug clusters.
• Experience with Kubeflow Pipelines or Vertex AI Pipelines and Airflow.
• GitOps for infra and CI/CD for model deployment.
• Production-grade Python, testing, packaging.
• Platform mindset with self-service tooling and SLOs.
• Ability to own a company-wide platform independently.

Responsibilities

• Own the machine learning platform infrastructure as part of the Data Infrastructure team.
• Manage Vertex AI, Kubeflow Pipelines, and GKE-based training/serving infra.
• Build templates, CI/CD, and self-service workflows for model shipping.
• Oversee model registry, versioning, deployment, and monitoring for drift.
• Support feature and training data flows across BigQuery and Airflow.
• Apply GitOps with Config Sync and enforce least-privilege access.
• Manage GPU and compute usage, quotas, and cost visibility.
• Own end-to-end platform used by vertical teams to build/train/serve models.

Skills

MLOps

Production ML infra

GCP Vertex AI

GKE

Kubernetes

Kubeflow Pipelines

Airflow

GitOps

CI/CD

Python

Self-service tooling

SLOs

Tools

Vertex AI

GKE

BigQuery

Kubernetes

Airflow

Kubeflow Pipelines

Job description

Xebia in Europe is seeking an experienced MLOps Platform Engineer to own the company's machine learning platform infrastructure. You will manage Vertex AI, Kubeflow Pipelines, and GKE-based training and serving, building templates, CI/CD, and self-service workflows that let data scientists ship models without tickets.

You will oversee model lifecycle, feature/data flows with BigQuery and Airflow, implement GitOps, and ensure security and cost efficiency.